.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/scenario_adapter/plot_multistart_example.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_scenario_adapter_plot_multistart_example.py: Multistart optimization ======================= Runs simple optimization problem with multiple starting points Nests an :class:`.MDOScenario` in a :class:`.DOEScenario` using an :class:`.MDOScenarioAdapter`. .. GENERATED FROM PYTHON SOURCE LINES 29-41 .. code-block:: Python from __future__ import annotations from gemseo import configure_logger from gemseo import create_design_space from gemseo import create_discipline from gemseo import create_scenario from gemseo.disciplines.scenario_adapters.mdo_scenario_adapter import MDOScenarioAdapter configure_logger() .. rst-class:: sphx-glr-script-out .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 42-44 Create the disciplines ---------------------- .. GENERATED FROM PYTHON SOURCE LINES 44-49 .. code-block:: Python objective = create_discipline("AnalyticDiscipline", expressions={"obj": "x**3-x+1"}) constraint = create_discipline( "AnalyticDiscipline", expressions={"cstr": "x**2+obj**2-1.5"} ) .. GENERATED FROM PYTHON SOURCE LINES 50-52 Create the design space ----------------------- .. GENERATED FROM PYTHON SOURCE LINES 52-55 .. code-block:: Python design_space = create_design_space() design_space.add_variable("x", l_b=-1.5, u_b=1.5, value=1.5) .. GENERATED FROM PYTHON SOURCE LINES 56-58 Create the MDO scenario ----------------------- .. GENERATED FROM PYTHON SOURCE LINES 58-67 .. code-block:: Python scenario = create_scenario( [objective, constraint], "DisciplinaryOpt", "obj", design_space, ) scenario.default_inputs = {"algo": "SLSQP", "max_iter": 10} scenario.add_constraint("cstr", constraint_type="ineq") .. GENERATED FROM PYTHON SOURCE LINES 68-70 Create the scenario adapter --------------------------- .. GENERATED FROM PYTHON SOURCE LINES 70-75 .. code-block:: Python dv_names = scenario.formulation.opt_problem.design_space.variable_names adapter = MDOScenarioAdapter( scenario, dv_names, ["obj", "cstr"], set_x0_before_opt=True ) .. GENERATED FROM PYTHON SOURCE LINES 76-78 Create the DOE scenario ----------------------- .. GENERATED FROM PYTHON SOURCE LINES 78-89 .. code-block:: Python scenario_doe = create_scenario( adapter, "DisciplinaryOpt", "obj", design_space, scenario_type="DOE", ) scenario_doe.add_constraint("cstr", constraint_type="ineq") run_inputs = {"n_samples": 10, "algo": "fullfact"} scenario_doe.execute(run_inputs) .. rst-class:: sphx-glr-script-out .. code-block:: none INFO - 00:11:18: INFO - 00:11:18: *** Start DOEScenario execution *** INFO - 00:11:18: DOEScenario INFO - 00:11:18: Disciplines: MDOScenario_adapter INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 1.5 | 1.5 | float | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm fullfact: INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.5 | 1.5 | float | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 161.48 it/sec, obj=-0.875] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 191.85 it/sec, obj=-0.267] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 250.51 it/sec, obj=-0.809] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 294.39 it/sec, obj=-0.868] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 328.91 it/sec, obj=-0.872] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 337.51 it/sec, obj=-0.265] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 341.59 it/sec, obj=0.136] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 345.95 it/sec, obj=0.579] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 363.77 it/sec, obj=0.289] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 364.85 it/sec, obj=1.25] WARNING - 00:11:18: Optimization found no feasible point ! The least infeasible point is selected. INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: WARNING - 00:11:18: The solution is not feasible. INFO - 00:11:18: Objective: 0.2888129873625884 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = 0.1513713660745195 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.252181466244097 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.040803) *** INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 21.61 it/sec, obj=0.289] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.166666666666667 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 926.51 it/sec, obj=0.579] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 425.54 it/sec, obj=-0.875] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 416.83 it/sec, obj=-0.267] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 453.30 it/sec, obj=-0.809] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 480.44 it/sec, obj=-0.868] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 500.28 it/sec, obj=-0.874] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 478.94 it/sec, obj=-0.266] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 463.54 it/sec, obj=0.135] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 454.11 it/sec, obj=0.577] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 467.64 it/sec, obj=0.288] WARNING - 00:11:18: Optimization found no feasible point ! The least infeasible point is selected. INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: WARNING - 00:11:18: The solution is not feasible. INFO - 00:11:18: Objective: 0.28811314244670916 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = 0.15144075010172386 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.252370379421043 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.033954) *** INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 24.53 it/sec, obj=0.288] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -0.8333333333333334 | 1.5 | float | INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 934.98 it/sec, obj=1.25] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 441.32 it/sec, obj=-0.875] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 498.49 it/sec, obj=1.01] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 467.51 it/sec, obj=-0.875] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 493.51 it/sec, obj=0.819] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 474.47 it/sec, obj=-0.875] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 486.31 it/sec, obj=0.693] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 471.20 it/sec, obj=-0.875] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 483.75 it/sec, obj=0.584] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 471.38 it/sec, obj=-0.875] WARNING - 00:11:18: Optimization found no feasible point ! The least infeasible point is selected. INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: WARNING - 00:11:18: The solution is not feasible. INFO - 00:11:18: Objective: 0.5837798748832244 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = 0.19806414473664136 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.165017254128868 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.032545) *** INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 25.82 it/sec, obj=0.584] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -0.5 | 1.5 | float | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 970.01 it/sec, obj=1.38] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 444.24 it/sec, obj=2.88] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 504.16 it/sec, obj=1.23] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 465.48 it/sec, obj=2.87] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 493.91 it/sec, obj=0.848] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 466.49 it/sec, obj=0.658] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 440.96 it/sec, obj=0.643] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 424.69 it/sec, obj=0.616] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 414.38 it/sec, obj=0.615] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 406.15 it/sec, obj=0.615] INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 13 INFO - 00:11:18: Solution: INFO - 00:11:18: The solution is feasible. INFO - 00:11:18: Objective: 0.6150998219543254 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = -0.788285881879476 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.5773788419679762 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.036910) *** INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 25.92 it/sec, obj=0.615] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -0.1666666666666667 | 1.5 | float | INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 952.60 it/sec, obj=1.16] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 438.07 it/sec, obj=2.87] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 497.41 it/sec, obj=0.785] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 443.34 it/sec, obj=2.88] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 457.10 it/sec, obj=0.644] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 433.50 it/sec, obj=0.624] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 416.58 it/sec, obj=0.615] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 404.59 it/sec, obj=0.615] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 395.36 it/sec, obj=0.615] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 389.24 it/sec, obj=0.615] INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: INFO - 00:11:18: The solution is feasible. INFO - 00:11:18: Objective: 0.6150998205402495 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = -0.7883188793606977 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.5773502675245377 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.038216) *** INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 25.81 it/sec, obj=0.615] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.1666666666666667 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 904.72 it/sec, obj=0.838] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 435.16 it/sec, obj=2.88] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 496.23 it/sec, obj=0.656] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 447.43 it/sec, obj=0.639] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 421.85 it/sec, obj=0.616] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 405.08 it/sec, obj=0.615] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 390.77 it/sec, obj=0.615] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 382.89 it/sec, obj=0.615] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 378.73 it/sec, obj=0.615] INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 10 INFO - 00:11:18: Solution: INFO - 00:11:18: The solution is feasible. INFO - 00:11:18: Objective: 0.6150998205402508 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = -0.7883189092934597 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.5773502416020033 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.034555) *** INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 26.05 it/sec, obj=0.615] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.5 | 1.5 | float | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 923.86 it/sec, obj=0.625] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 431.93 it/sec, obj=2.87] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 489.68 it/sec, obj=0.616] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 435.29 it/sec, obj=0.615] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 409.30 it/sec, obj=0.615] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 397.97 it/sec, obj=0.615] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 389.25 it/sec, obj=0.615] INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Successive iterates of the objective function are closer than ftol_rel or ftol_abs. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 8 INFO - 00:11:18: Solution: INFO - 00:11:18: The solution is feasible. INFO - 00:11:18: Objective: 0.6150998205402526 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = -0.7883188285028959 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.5773503115686811 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.028645) *** INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 26.82 it/sec, obj=0.615] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.8333333333333335 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 950.44 it/sec, obj=0.745] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 436.34 it/sec, obj=-0.875] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 421.76 it/sec, obj=-0.267] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 438.25 it/sec, obj=-0.809] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 463.97 it/sec, obj=-0.868] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 486.98 it/sec, obj=-0.874] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 468.14 it/sec, obj=-0.266] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 453.23 it/sec, obj=0.135] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 445.15 it/sec, obj=0.577] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 458.16 it/sec, obj=0.288] INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: INFO - 00:11:18: The solution is feasible. INFO - 00:11:18: Objective: 0.7453703703703706 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = -0.2499785665294918 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 0.8333333333333335 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.034011) *** INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 26.92 it/sec, obj=0.745] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+-------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+-------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 1.166666666666667 | 1.5 | float | INFO - 00:11:18: +------+-------------+-------------------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 949.37 it/sec, obj=1.42] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 435.66 it/sec, obj=-0.875] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 421.20 it/sec, obj=-0.267] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 459.31 it/sec, obj=-0.809] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 486.26 it/sec, obj=-0.868] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 505.60 it/sec, obj=-0.874] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 483.48 it/sec, obj=-0.266] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 436.12 it/sec, obj=0.135] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 427.72 it/sec, obj=0.577] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 441.11 it/sec, obj=0.288] WARNING - 00:11:18: Optimization found no feasible point ! The least infeasible point is selected. INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: WARNING - 00:11:18: The solution is not feasible. INFO - 00:11:18: Objective: 0.28811314244698893 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = 0.1514407501016959 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.252370379420967 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.035098) *** INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 26.99 it/sec, obj=0.288] INFO - 00:11:18: INFO - 00:11:18: *** Start MDOScenario execution *** INFO - 00:11:18: MDOScenario INFO - 00:11:18: Disciplines: AnalyticDiscipline AnalyticDiscipline INFO - 00:11:18: MDO formulation: DisciplinaryOpt INFO - 00:11:18: Optimization problem: INFO - 00:11:18: minimize obj(x) INFO - 00:11:18: with respect to x INFO - 00:11:18: subject to constraints: INFO - 00:11:18: cstr(x) <= 0.0 INFO - 00:11:18: over the design space: INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | 1.5 | 1.5 | float | INFO - 00:11:18: +------+-------------+-------+-------------+-------+ INFO - 00:11:18: Solving optimization problem with algorithm SLSQP: INFO - 00:11:18: 10%|█ | 1/10 [00:00<00:00, 918.59 it/sec, obj=2.88] INFO - 00:11:18: 20%|██ | 2/10 [00:00<00:00, 433.56 it/sec, obj=-0.875] INFO - 00:11:18: 30%|███ | 3/10 [00:00<00:00, 420.50 it/sec, obj=-0.267] INFO - 00:11:18: 40%|████ | 4/10 [00:00<00:00, 460.32 it/sec, obj=-0.809] INFO - 00:11:18: 50%|█████ | 5/10 [00:00<00:00, 486.57 it/sec, obj=-0.868] INFO - 00:11:18: 60%|██████ | 6/10 [00:00<00:00, 508.32 it/sec, obj=-0.874] INFO - 00:11:18: 70%|███████ | 7/10 [00:00<00:00, 485.43 it/sec, obj=-0.266] INFO - 00:11:18: 80%|████████ | 8/10 [00:00<00:00, 469.92 it/sec, obj=0.135] INFO - 00:11:18: 90%|█████████ | 9/10 [00:00<00:00, 459.16 it/sec, obj=0.577] INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 472.04 it/sec, obj=0.288] WARNING - 00:11:18: Optimization found no feasible point ! The least infeasible point is selected. INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: Maximum number of iterations reached. GEMSEO Stopped the driver INFO - 00:11:18: Number of calls to the objective function by the optimizer: 12 INFO - 00:11:18: Solution: WARNING - 00:11:18: The solution is not feasible. INFO - 00:11:18: Objective: 0.28811314244587316 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = 0.15144075010180735 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -1.252370379421268 | 1.5 | float | INFO - 00:11:18: +------+-------------+--------------------+-------------+-------+ INFO - 00:11:18: *** End MDOScenario execution (time: 0:00:00.033622) *** INFO - 00:11:18: 100%|██████████| 10/10 [00:00<00:00, 27.15 it/sec, obj=0.288] INFO - 00:11:18: Optimization result: INFO - 00:11:18: Optimizer info: INFO - 00:11:18: Status: None INFO - 00:11:18: Message: None INFO - 00:11:18: Number of calls to the objective function by the optimizer: 10 INFO - 00:11:18: Solution: INFO - 00:11:18: The solution is feasible. INFO - 00:11:18: Objective: 0.6150998205402495 INFO - 00:11:18: Standardized constraints: INFO - 00:11:18: cstr = -0.7883188793606977 INFO - 00:11:18: Design space: INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: | Name | Lower bound | Value | Upper bound | Type | INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: | x | -1.5 | -0.1666666666666667 | 1.5 | float | INFO - 00:11:18: +------+-------------+---------------------+-------------+-------+ INFO - 00:11:18: *** End DOEScenario execution (time: 0:00:00.380876) *** {'eval_jac': False, 'n_samples': 10, 'algo': 'fullfact'} .. GENERATED FROM PYTHON SOURCE LINES 90-92 Plot the optimum objective for different x0 ------------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 92-93 .. code-block:: Python scenario_doe.post_process("BasicHistory", variable_names=["obj"], save=False, show=True) .. image-sg:: /examples/scenario_adapter/images/sphx_glr_plot_multistart_example_001.png :alt: History plot :srcset: /examples/scenario_adapter/images/sphx_glr_plot_multistart_example_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.583 seconds) .. _sphx_glr_download_examples_scenario_adapter_plot_multistart_example.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_multistart_example.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_multistart_example.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_